Upload folder using huggingface_hub
Browse files- best_eval_results.txt +9 -0
- config.json +29 -0
- eval_results.txt +900 -0
- pytorch_model.bin +3 -0
- vocab.txt +0 -0
best_eval_results.txt
ADDED
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att_loss = 0.0
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cls_loss = 2.1959577999819784
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corr = 0.8030687544861099
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eval_loss = 0.9703495565881121
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global_step = 1299
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loss = 2.1959577999819784
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pearson = 0.7943542
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rep_loss = 0.0
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spearmanr = 0.8117833086090606
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config.json
ADDED
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{
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"cell": {},
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"classifier_dropout": null,
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"dtype": "float32",
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"emb_size": 312,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 312,
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"initializer_range": 0.02,
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"intermediate_size": 1200,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 4,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"pre_trained": "",
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"structure": [],
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"training": "",
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"transformers_version": "4.57.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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eval_results.txt
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|
| 1 |
+
att_loss = 0.0
|
| 2 |
+
cls_loss = 9.005364239817919
|
| 3 |
+
corr = 0.4300948107191611
|
| 4 |
+
eval_loss = 6.261911371920971
|
| 5 |
+
global_step = 99
|
| 6 |
+
loss = 9.005364239817919
|
| 7 |
+
pearson = 0.48089385
|
| 8 |
+
rep_loss = 0.0
|
| 9 |
+
spearmanr = 0.3792957711117842
|
| 10 |
+
att_loss = 0.0
|
| 11 |
+
cls_loss = 7.687891845128045
|
| 12 |
+
corr = 0.38950787103451145
|
| 13 |
+
eval_loss = 3.903873103730222
|
| 14 |
+
global_step = 199
|
| 15 |
+
loss = 7.687891845128045
|
| 16 |
+
pearson = 0.40832373
|
| 17 |
+
rep_loss = 0.0
|
| 18 |
+
spearmanr = 0.3706920070703199
|
| 19 |
+
att_loss = 0.0
|
| 20 |
+
cls_loss = 6.37817909765403
|
| 21 |
+
corr = 0.543543798128133
|
| 22 |
+
eval_loss = 2.1876264430106955
|
| 23 |
+
global_step = 299
|
| 24 |
+
loss = 6.37817909765403
|
| 25 |
+
pearson = 0.5556736
|
| 26 |
+
rep_loss = 0.0
|
| 27 |
+
spearmanr = 0.5314139970131019
|
| 28 |
+
att_loss = 0.0
|
| 29 |
+
cls_loss = 5.285703499514358
|
| 30 |
+
corr = 0.616451454910093
|
| 31 |
+
eval_loss = 1.4939240635709559
|
| 32 |
+
global_step = 399
|
| 33 |
+
loss = 5.285703499514358
|
| 34 |
+
pearson = 0.6096582
|
| 35 |
+
rep_loss = 0.0
|
| 36 |
+
spearmanr = 0.623244728152858
|
| 37 |
+
att_loss = 0.0
|
| 38 |
+
cls_loss = 4.490578535802379
|
| 39 |
+
corr = 0.7218131077527101
|
| 40 |
+
eval_loss = 1.260880209664081
|
| 41 |
+
global_step = 499
|
| 42 |
+
loss = 4.490578535802379
|
| 43 |
+
pearson = 0.7010848
|
| 44 |
+
rep_loss = 0.0
|
| 45 |
+
spearmanr = 0.7425414228914372
|
| 46 |
+
att_loss = 0.0
|
| 47 |
+
cls_loss = 3.911254790171558
|
| 48 |
+
corr = 0.754601825992748
|
| 49 |
+
eval_loss = 1.4121818263480004
|
| 50 |
+
global_step = 599
|
| 51 |
+
loss = 3.911254790171558
|
| 52 |
+
pearson = 0.71077013
|
| 53 |
+
rep_loss = 0.0
|
| 54 |
+
spearmanr = 0.7984335218280255
|
| 55 |
+
att_loss = 0.0
|
| 56 |
+
cls_loss = 3.4808279432793374
|
| 57 |
+
corr = 0.7677782075922555
|
| 58 |
+
eval_loss = 1.327657496675532
|
| 59 |
+
global_step = 699
|
| 60 |
+
loss = 3.4808279432793374
|
| 61 |
+
pearson = 0.7354496
|
| 62 |
+
rep_loss = 0.0
|
| 63 |
+
spearmanr = 0.8001068030438555
|
| 64 |
+
att_loss = 0.0
|
| 65 |
+
cls_loss = 3.1460038052034913
|
| 66 |
+
corr = 0.7779408480313847
|
| 67 |
+
eval_loss = 1.197221781979216
|
| 68 |
+
global_step = 799
|
| 69 |
+
loss = 3.1460038052034913
|
| 70 |
+
pearson = 0.75245035
|
| 71 |
+
rep_loss = 0.0
|
| 72 |
+
spearmanr = 0.8034313491160533
|
| 73 |
+
att_loss = 0.0
|
| 74 |
+
cls_loss = 2.8815531456165506
|
| 75 |
+
corr = 0.8022246323238583
|
| 76 |
+
eval_loss = 1.3076959062129894
|
| 77 |
+
global_step = 899
|
| 78 |
+
loss = 2.8815531456165506
|
| 79 |
+
pearson = 0.777015
|
| 80 |
+
rep_loss = 0.0
|
| 81 |
+
spearmanr = 0.8274342938682977
|
| 82 |
+
att_loss = 0.0
|
| 83 |
+
cls_loss = 2.6619408019670137
|
| 84 |
+
corr = 0.7994548055555308
|
| 85 |
+
eval_loss = 1.3583446392353544
|
| 86 |
+
global_step = 999
|
| 87 |
+
loss = 2.6619408019670137
|
| 88 |
+
pearson = 0.7800855
|
| 89 |
+
rep_loss = 0.0
|
| 90 |
+
spearmanr = 0.8188241070560385
|
| 91 |
+
att_loss = 0.0
|
| 92 |
+
cls_loss = 2.480926227743133
|
| 93 |
+
corr = 0.7664423166157106
|
| 94 |
+
eval_loss = 1.512548692682956
|
| 95 |
+
global_step = 1099
|
| 96 |
+
loss = 2.480926227743133
|
| 97 |
+
pearson = 0.7402985
|
| 98 |
+
rep_loss = 0.0
|
| 99 |
+
spearmanr = 0.7925861236336429
|
| 100 |
+
att_loss = 0.0
|
| 101 |
+
cls_loss = 2.326544588709792
|
| 102 |
+
corr = 0.7817302061271746
|
| 103 |
+
eval_loss = 1.3125593681284722
|
| 104 |
+
global_step = 1199
|
| 105 |
+
loss = 2.326544588709792
|
| 106 |
+
pearson = 0.76982266
|
| 107 |
+
rep_loss = 0.0
|
| 108 |
+
spearmanr = 0.7936377551460423
|
| 109 |
+
att_loss = 0.0
|
| 110 |
+
cls_loss = 2.1959577999819784
|
| 111 |
+
corr = 0.8030687544861099
|
| 112 |
+
eval_loss = 0.9703495565881121
|
| 113 |
+
global_step = 1299
|
| 114 |
+
loss = 2.1959577999819784
|
| 115 |
+
pearson = 0.7943542
|
| 116 |
+
rep_loss = 0.0
|
| 117 |
+
spearmanr = 0.8117833086090606
|
| 118 |
+
att_loss = 0.0
|
| 119 |
+
cls_loss = 2.0814725547027724
|
| 120 |
+
corr = 0.7997198568840136
|
| 121 |
+
eval_loss = 1.0843563491993762
|
| 122 |
+
global_step = 1399
|
| 123 |
+
loss = 2.0814725547027724
|
| 124 |
+
pearson = 0.7857965
|
| 125 |
+
rep_loss = 0.0
|
| 126 |
+
spearmanr = 0.81364319067385
|
| 127 |
+
att_loss = 0.0
|
| 128 |
+
cls_loss = 1.9812077716082395
|
| 129 |
+
corr = 0.7947387072348856
|
| 130 |
+
eval_loss = 1.2983285898857928
|
| 131 |
+
global_step = 1499
|
| 132 |
+
loss = 1.9812077716082395
|
| 133 |
+
pearson = 0.78100586
|
| 134 |
+
rep_loss = 0.0
|
| 135 |
+
spearmanr = 0.8084715550947712
|
| 136 |
+
att_loss = 0.0
|
| 137 |
+
cls_loss = 1.8918808762955621
|
| 138 |
+
corr = 0.7911425634777823
|
| 139 |
+
eval_loss = 1.336884728137483
|
| 140 |
+
global_step = 1599
|
| 141 |
+
loss = 1.8918808762955621
|
| 142 |
+
pearson = 0.77525187
|
| 143 |
+
rep_loss = 0.0
|
| 144 |
+
spearmanr = 0.8070332615686018
|
| 145 |
+
att_loss = 0.0
|
| 146 |
+
cls_loss = 1.8102179452680434
|
| 147 |
+
corr = 0.7729807460511025
|
| 148 |
+
eval_loss = 1.400628296618766
|
| 149 |
+
global_step = 1699
|
| 150 |
+
loss = 1.8102179452680434
|
| 151 |
+
pearson = 0.75579536
|
| 152 |
+
rep_loss = 0.0
|
| 153 |
+
spearmanr = 0.7901661324906936
|
| 154 |
+
att_loss = 0.0
|
| 155 |
+
cls_loss = 1.7371201205743956
|
| 156 |
+
corr = 0.7512980805816813
|
| 157 |
+
eval_loss = 1.8098871936189367
|
| 158 |
+
global_step = 1799
|
| 159 |
+
loss = 1.7371201205743956
|
| 160 |
+
pearson = 0.7338536
|
| 161 |
+
rep_loss = 0.0
|
| 162 |
+
spearmanr = 0.7687425825958579
|
| 163 |
+
att_loss = 0.0
|
| 164 |
+
cls_loss = 1.6735850952059548
|
| 165 |
+
corr = 0.7674272300127196
|
| 166 |
+
eval_loss = 1.4597826130846714
|
| 167 |
+
global_step = 1899
|
| 168 |
+
loss = 1.6735850952059548
|
| 169 |
+
pearson = 0.75391865
|
| 170 |
+
rep_loss = 0.0
|
| 171 |
+
spearmanr = 0.7809358122593261
|
| 172 |
+
att_loss = 0.0
|
| 173 |
+
cls_loss = 1.6122812697176578
|
| 174 |
+
corr = 0.7496080853766286
|
| 175 |
+
eval_loss = 1.431902787786849
|
| 176 |
+
global_step = 1999
|
| 177 |
+
loss = 1.6122812697176578
|
| 178 |
+
pearson = 0.73915076
|
| 179 |
+
rep_loss = 0.0
|
| 180 |
+
spearmanr = 0.7600654081952738
|
| 181 |
+
att_loss = 0.0
|
| 182 |
+
cls_loss = 1.557993867323193
|
| 183 |
+
corr = 0.7639387388022303
|
| 184 |
+
eval_loss = 1.4140621411039473
|
| 185 |
+
global_step = 2099
|
| 186 |
+
loss = 1.557993867323193
|
| 187 |
+
pearson = 0.75430703
|
| 188 |
+
rep_loss = 0.0
|
| 189 |
+
spearmanr = 0.7735704459729908
|
| 190 |
+
att_loss = 0.0
|
| 191 |
+
cls_loss = 1.5079209370036297
|
| 192 |
+
corr = 0.7361398032687032
|
| 193 |
+
eval_loss = 1.66468449983191
|
| 194 |
+
global_step = 2199
|
| 195 |
+
loss = 1.5079209370036297
|
| 196 |
+
pearson = 0.7219286
|
| 197 |
+
rep_loss = 0.0
|
| 198 |
+
spearmanr = 0.7503510100408243
|
| 199 |
+
att_loss = 0.0
|
| 200 |
+
cls_loss = 1.4611414592776313
|
| 201 |
+
corr = 0.7276611276546883
|
| 202 |
+
eval_loss = 1.6157480471945824
|
| 203 |
+
global_step = 2299
|
| 204 |
+
loss = 1.4611414592776313
|
| 205 |
+
pearson = 0.71724665
|
| 206 |
+
rep_loss = 0.0
|
| 207 |
+
spearmanr = 0.7380756036599014
|
| 208 |
+
att_loss = 0.0
|
| 209 |
+
cls_loss = 1.4175528425097514
|
| 210 |
+
corr = 0.7672389675814649
|
| 211 |
+
eval_loss = 1.5186812738154798
|
| 212 |
+
global_step = 2399
|
| 213 |
+
loss = 1.4175528425097514
|
| 214 |
+
pearson = 0.757766
|
| 215 |
+
rep_loss = 0.0
|
| 216 |
+
spearmanr = 0.7767119267858547
|
| 217 |
+
att_loss = 0.0
|
| 218 |
+
cls_loss = 1.3789727804409404
|
| 219 |
+
corr = 0.7487155297570924
|
| 220 |
+
eval_loss = 1.599209355547073
|
| 221 |
+
global_step = 2499
|
| 222 |
+
loss = 1.3789727804409404
|
| 223 |
+
pearson = 0.73809224
|
| 224 |
+
rep_loss = 0.0
|
| 225 |
+
spearmanr = 0.7593388158427677
|
| 226 |
+
att_loss = 0.0
|
| 227 |
+
cls_loss = 1.3409868198410737
|
| 228 |
+
corr = 0.7449651419212044
|
| 229 |
+
eval_loss = 1.6820716166749914
|
| 230 |
+
global_step = 2599
|
| 231 |
+
loss = 1.3409868198410737
|
| 232 |
+
pearson = 0.73386365
|
| 233 |
+
rep_loss = 0.0
|
| 234 |
+
spearmanr = 0.756066632089937
|
| 235 |
+
att_loss = 0.0
|
| 236 |
+
cls_loss = 1.3068375978625761
|
| 237 |
+
corr = 0.7347656701616516
|
| 238 |
+
eval_loss = 1.693367508497644
|
| 239 |
+
global_step = 2699
|
| 240 |
+
loss = 1.3068375978625761
|
| 241 |
+
pearson = 0.7225629
|
| 242 |
+
rep_loss = 0.0
|
| 243 |
+
spearmanr = 0.7469684311970216
|
| 244 |
+
att_loss = 0.0
|
| 245 |
+
cls_loss = 1.2746448926401377
|
| 246 |
+
corr = 0.7470871425392092
|
| 247 |
+
eval_loss = 1.4426170023197824
|
| 248 |
+
global_step = 2799
|
| 249 |
+
loss = 1.2746448926401377
|
| 250 |
+
pearson = 0.73833716
|
| 251 |
+
rep_loss = 0.0
|
| 252 |
+
spearmanr = 0.7558371259216189
|
| 253 |
+
att_loss = 0.0
|
| 254 |
+
cls_loss = 1.2434133802325038
|
| 255 |
+
corr = 0.737346086521655
|
| 256 |
+
eval_loss = 1.4622940376717994
|
| 257 |
+
global_step = 2899
|
| 258 |
+
loss = 1.2434133802325038
|
| 259 |
+
pearson = 0.7299944
|
| 260 |
+
rep_loss = 0.0
|
| 261 |
+
spearmanr = 0.7446977568064325
|
| 262 |
+
att_loss = 0.0
|
| 263 |
+
cls_loss = 1.2139794980040706
|
| 264 |
+
corr = 0.7124756000838279
|
| 265 |
+
eval_loss = 1.8439517528452771
|
| 266 |
+
global_step = 2999
|
| 267 |
+
loss = 1.2139794980040706
|
| 268 |
+
pearson = 0.69962585
|
| 269 |
+
rep_loss = 0.0
|
| 270 |
+
spearmanr = 0.72532535044384
|
| 271 |
+
att_loss = 0.0
|
| 272 |
+
cls_loss = 1.1867008409593598
|
| 273 |
+
corr = 0.7302273754066719
|
| 274 |
+
eval_loss = 1.9274177551269531
|
| 275 |
+
global_step = 3099
|
| 276 |
+
loss = 1.1867008409593598
|
| 277 |
+
pearson = 0.71357024
|
| 278 |
+
rep_loss = 0.0
|
| 279 |
+
spearmanr = 0.7468845136536147
|
| 280 |
+
att_loss = 0.0
|
| 281 |
+
cls_loss = 1.1605635167062562
|
| 282 |
+
corr = 0.7384751647149297
|
| 283 |
+
eval_loss = 1.559603842649054
|
| 284 |
+
global_step = 3199
|
| 285 |
+
loss = 1.1605635167062562
|
| 286 |
+
pearson = 0.7293106
|
| 287 |
+
rep_loss = 0.0
|
| 288 |
+
spearmanr = 0.74763975728249
|
| 289 |
+
att_loss = 0.0
|
| 290 |
+
cls_loss = 1.1357824253011524
|
| 291 |
+
corr = 0.7258406533962493
|
| 292 |
+
eval_loss = 1.5974246662981966
|
| 293 |
+
global_step = 3299
|
| 294 |
+
loss = 1.1357824253011524
|
| 295 |
+
pearson = 0.71761805
|
| 296 |
+
rep_loss = 0.0
|
| 297 |
+
spearmanr = 0.734063258601428
|
| 298 |
+
att_loss = 0.0
|
| 299 |
+
cls_loss = 1.1132933739863202
|
| 300 |
+
corr = 0.7321920748098905
|
| 301 |
+
eval_loss = 1.34926072523949
|
| 302 |
+
global_step = 3399
|
| 303 |
+
loss = 1.1132933739863202
|
| 304 |
+
pearson = 0.72970617
|
| 305 |
+
rep_loss = 0.0
|
| 306 |
+
spearmanr = 0.7346779814450372
|
| 307 |
+
att_loss = 0.0
|
| 308 |
+
cls_loss = 1.0915653434147934
|
| 309 |
+
corr = 0.7087784086791448
|
| 310 |
+
eval_loss = 1.9778355315644691
|
| 311 |
+
global_step = 3499
|
| 312 |
+
loss = 1.0915653434147934
|
| 313 |
+
pearson = 0.69653547
|
| 314 |
+
rep_loss = 0.0
|
| 315 |
+
spearmanr = 0.7210213492567881
|
| 316 |
+
att_loss = 0.0
|
| 317 |
+
cls_loss = 1.0701567433664751
|
| 318 |
+
corr = 0.7173621979088511
|
| 319 |
+
eval_loss = 1.8300747788966971
|
| 320 |
+
global_step = 3599
|
| 321 |
+
loss = 1.0701567433664751
|
| 322 |
+
pearson = 0.7088069
|
| 323 |
+
rep_loss = 0.0
|
| 324 |
+
spearmanr = 0.7259175234498433
|
| 325 |
+
att_loss = 0.0
|
| 326 |
+
cls_loss = 1.0502434219459031
|
| 327 |
+
corr = 0.7323512632760808
|
| 328 |
+
eval_loss = 1.4830917050229742
|
| 329 |
+
global_step = 3699
|
| 330 |
+
loss = 1.0502434219459031
|
| 331 |
+
pearson = 0.7267473
|
| 332 |
+
rep_loss = 0.0
|
| 333 |
+
spearmanr = 0.7379552521533579
|
| 334 |
+
att_loss = 0.0
|
| 335 |
+
cls_loss = 1.031378848450251
|
| 336 |
+
corr = 0.7042696008220591
|
| 337 |
+
eval_loss = 1.7919619635064552
|
| 338 |
+
global_step = 3799
|
| 339 |
+
loss = 1.031378848450251
|
| 340 |
+
pearson = 0.6978699
|
| 341 |
+
rep_loss = 0.0
|
| 342 |
+
spearmanr = 0.7106693047553854
|
| 343 |
+
att_loss = 0.0
|
| 344 |
+
cls_loss = 1.012465915540207
|
| 345 |
+
corr = 0.702614859723682
|
| 346 |
+
eval_loss = 1.652784289197719
|
| 347 |
+
global_step = 3899
|
| 348 |
+
loss = 1.012465915540207
|
| 349 |
+
pearson = 0.6947644
|
| 350 |
+
rep_loss = 0.0
|
| 351 |
+
spearmanr = 0.7104653437607185
|
| 352 |
+
att_loss = 0.0
|
| 353 |
+
cls_loss = 0.9950689477424498
|
| 354 |
+
corr = 0.7206360784010446
|
| 355 |
+
eval_loss = 1.731373152834304
|
| 356 |
+
global_step = 3999
|
| 357 |
+
loss = 0.9950689477424498
|
| 358 |
+
pearson = 0.7135711
|
| 359 |
+
rep_loss = 0.0
|
| 360 |
+
spearmanr = 0.7277010851773335
|
| 361 |
+
att_loss = 0.0
|
| 362 |
+
cls_loss = 0.9788163769613042
|
| 363 |
+
corr = 0.714318527216541
|
| 364 |
+
eval_loss = 1.7111480286780825
|
| 365 |
+
global_step = 4099
|
| 366 |
+
loss = 0.9788163769613042
|
| 367 |
+
pearson = 0.7090455
|
| 368 |
+
rep_loss = 0.0
|
| 369 |
+
spearmanr = 0.7195915250675424
|
| 370 |
+
att_loss = 0.0
|
| 371 |
+
cls_loss = 0.9622233910581475
|
| 372 |
+
corr = 0.6853242717502325
|
| 373 |
+
eval_loss = 1.7859996107030423
|
| 374 |
+
global_step = 4199
|
| 375 |
+
loss = 0.9622233910581475
|
| 376 |
+
pearson = 0.6814705
|
| 377 |
+
rep_loss = 0.0
|
| 378 |
+
spearmanr = 0.6891780301566539
|
| 379 |
+
att_loss = 0.0
|
| 380 |
+
cls_loss = 0.9471831875769835
|
| 381 |
+
corr = 0.7131559283800115
|
| 382 |
+
eval_loss = 1.622054821633278
|
| 383 |
+
global_step = 4299
|
| 384 |
+
loss = 0.9471831875769835
|
| 385 |
+
pearson = 0.7090949
|
| 386 |
+
rep_loss = 0.0
|
| 387 |
+
spearmanr = 0.7172169747486093
|
| 388 |
+
att_loss = 0.0
|
| 389 |
+
cls_loss = 0.9329939540285066
|
| 390 |
+
corr = 0.6870643967077303
|
| 391 |
+
eval_loss = 1.8330216686776344
|
| 392 |
+
global_step = 4399
|
| 393 |
+
loss = 0.9329939540285066
|
| 394 |
+
pearson = 0.67788506
|
| 395 |
+
rep_loss = 0.0
|
| 396 |
+
spearmanr = 0.6962437378734686
|
| 397 |
+
att_loss = 0.0
|
| 398 |
+
cls_loss = 0.9183110792780219
|
| 399 |
+
corr = 0.7227940116094242
|
| 400 |
+
eval_loss = 1.3678106373928962
|
| 401 |
+
global_step = 4499
|
| 402 |
+
loss = 0.9183110792780219
|
| 403 |
+
pearson = 0.7182917
|
| 404 |
+
rep_loss = 0.0
|
| 405 |
+
spearmanr = 0.7272963233325265
|
| 406 |
+
att_loss = 0.0
|
| 407 |
+
cls_loss = 0.9043454090038132
|
| 408 |
+
corr = 0.7031386505600783
|
| 409 |
+
eval_loss = 1.654315320735282
|
| 410 |
+
global_step = 4599
|
| 411 |
+
loss = 0.9043454090038132
|
| 412 |
+
pearson = 0.69853574
|
| 413 |
+
rep_loss = 0.0
|
| 414 |
+
spearmanr = 0.7077415607446378
|
| 415 |
+
att_loss = 0.0
|
| 416 |
+
cls_loss = 0.8915996705091718
|
| 417 |
+
corr = 0.6912515424716605
|
| 418 |
+
eval_loss = 1.8133547566038497
|
| 419 |
+
global_step = 4699
|
| 420 |
+
loss = 0.8915996705091718
|
| 421 |
+
pearson = 0.68502086
|
| 422 |
+
rep_loss = 0.0
|
| 423 |
+
spearmanr = 0.6974822209334639
|
| 424 |
+
att_loss = 0.0
|
| 425 |
+
cls_loss = 0.8788705783139097
|
| 426 |
+
corr = 0.689750033582543
|
| 427 |
+
eval_loss = 1.833152491361537
|
| 428 |
+
global_step = 4799
|
| 429 |
+
loss = 0.8788705783139097
|
| 430 |
+
pearson = 0.68362486
|
| 431 |
+
rep_loss = 0.0
|
| 432 |
+
spearmanr = 0.6958752035405135
|
| 433 |
+
att_loss = 0.0
|
| 434 |
+
cls_loss = 0.8668866221391686
|
| 435 |
+
corr = 0.7031919755220644
|
| 436 |
+
eval_loss = 1.5557793239329725
|
| 437 |
+
global_step = 4899
|
| 438 |
+
loss = 0.8668866221391686
|
| 439 |
+
pearson = 0.69908214
|
| 440 |
+
rep_loss = 0.0
|
| 441 |
+
spearmanr = 0.7073018148899539
|
| 442 |
+
att_loss = 0.0
|
| 443 |
+
cls_loss = 0.8550884065511323
|
| 444 |
+
corr = 0.7002624177069314
|
| 445 |
+
eval_loss = 1.7266483719044543
|
| 446 |
+
global_step = 4999
|
| 447 |
+
loss = 0.8550884065511323
|
| 448 |
+
pearson = 0.6947645
|
| 449 |
+
rep_loss = 0.0
|
| 450 |
+
spearmanr = 0.7057603405179278
|
| 451 |
+
att_loss = 0.0
|
| 452 |
+
cls_loss = 0.8436031134371361
|
| 453 |
+
corr = 0.6758527351442294
|
| 454 |
+
eval_loss = 2.0720162049252937
|
| 455 |
+
global_step = 5099
|
| 456 |
+
loss = 0.8436031134371361
|
| 457 |
+
pearson = 0.6684816
|
| 458 |
+
rep_loss = 0.0
|
| 459 |
+
spearmanr = 0.6832238819248113
|
| 460 |
+
att_loss = 0.0
|
| 461 |
+
cls_loss = 0.8326283099302124
|
| 462 |
+
corr = 0.7132458234854024
|
| 463 |
+
eval_loss = 1.6419236609276304
|
| 464 |
+
global_step = 5199
|
| 465 |
+
loss = 0.8326283099302124
|
| 466 |
+
pearson = 0.70869005
|
| 467 |
+
rep_loss = 0.0
|
| 468 |
+
spearmanr = 0.7178015997067057
|
| 469 |
+
att_loss = 0.0
|
| 470 |
+
cls_loss = 0.8218213165367655
|
| 471 |
+
corr = 0.7085656519985153
|
| 472 |
+
eval_loss = 1.7091985554137128
|
| 473 |
+
global_step = 5299
|
| 474 |
+
loss = 0.8218213165367655
|
| 475 |
+
pearson = 0.703077
|
| 476 |
+
rep_loss = 0.0
|
| 477 |
+
spearmanr = 0.7140542857360749
|
| 478 |
+
att_loss = 0.0
|
| 479 |
+
cls_loss = 0.8110722276011447
|
| 480 |
+
corr = 0.7193177219171376
|
| 481 |
+
eval_loss = 1.5461978183147755
|
| 482 |
+
global_step = 5399
|
| 483 |
+
loss = 0.8110722276011447
|
| 484 |
+
pearson = 0.7156632
|
| 485 |
+
rep_loss = 0.0
|
| 486 |
+
spearmanr = 0.7229722491779033
|
| 487 |
+
att_loss = 0.0
|
| 488 |
+
cls_loss = 0.8010753031524014
|
| 489 |
+
corr = 0.7074498213425562
|
| 490 |
+
eval_loss = 1.7433819586926318
|
| 491 |
+
global_step = 5499
|
| 492 |
+
loss = 0.8010753031524014
|
| 493 |
+
pearson = 0.7020305
|
| 494 |
+
rep_loss = 0.0
|
| 495 |
+
spearmanr = 0.7128691627771229
|
| 496 |
+
att_loss = 0.0
|
| 497 |
+
cls_loss = 0.7916432439370716
|
| 498 |
+
corr = 0.7097677455717997
|
| 499 |
+
eval_loss = 1.5983693894553692
|
| 500 |
+
global_step = 5599
|
| 501 |
+
loss = 0.7916432439370716
|
| 502 |
+
pearson = 0.7039459
|
| 503 |
+
rep_loss = 0.0
|
| 504 |
+
spearmanr = 0.7155896159757525
|
| 505 |
+
att_loss = 0.0
|
| 506 |
+
cls_loss = 0.7823319543616503
|
| 507 |
+
corr = 0.7060972221765717
|
| 508 |
+
eval_loss = 1.5861609305473083
|
| 509 |
+
global_step = 5699
|
| 510 |
+
loss = 0.7823319543616503
|
| 511 |
+
pearson = 0.70183
|
| 512 |
+
rep_loss = 0.0
|
| 513 |
+
spearmanr = 0.7103644148655335
|
| 514 |
+
att_loss = 0.0
|
| 515 |
+
cls_loss = 0.7732199380833705
|
| 516 |
+
corr = 0.6890589107809071
|
| 517 |
+
eval_loss = 1.8573462233898488
|
| 518 |
+
global_step = 5799
|
| 519 |
+
loss = 0.7732199380833705
|
| 520 |
+
pearson = 0.68283415
|
| 521 |
+
rep_loss = 0.0
|
| 522 |
+
spearmanr = 0.6952836731548317
|
| 523 |
+
att_loss = 0.0
|
| 524 |
+
cls_loss = 0.7643341663135504
|
| 525 |
+
corr = 0.7058790472173033
|
| 526 |
+
eval_loss = 1.4386099982768932
|
| 527 |
+
global_step = 5899
|
| 528 |
+
loss = 0.7643341663135504
|
| 529 |
+
pearson = 0.7031361
|
| 530 |
+
rep_loss = 0.0
|
| 531 |
+
spearmanr = 0.7086220079706784
|
| 532 |
+
att_loss = 0.0
|
| 533 |
+
cls_loss = 0.7561885771295204
|
| 534 |
+
corr = 0.6788465339048545
|
| 535 |
+
eval_loss = 1.793242448187889
|
| 536 |
+
global_step = 5999
|
| 537 |
+
loss = 0.7561885771295204
|
| 538 |
+
pearson = 0.67619944
|
| 539 |
+
rep_loss = 0.0
|
| 540 |
+
spearmanr = 0.6814936316219649
|
| 541 |
+
att_loss = 0.0
|
| 542 |
+
cls_loss = 0.7476031216184249
|
| 543 |
+
corr = 0.7000766093512025
|
| 544 |
+
eval_loss = 1.5412416115720222
|
| 545 |
+
global_step = 6099
|
| 546 |
+
loss = 0.7476031216184249
|
| 547 |
+
pearson = 0.69730866
|
| 548 |
+
rep_loss = 0.0
|
| 549 |
+
spearmanr = 0.7028445591488772
|
| 550 |
+
att_loss = 0.0
|
| 551 |
+
cls_loss = 0.7393267748270146
|
| 552 |
+
corr = 0.6843219592579534
|
| 553 |
+
eval_loss = 1.711897778384229
|
| 554 |
+
global_step = 6199
|
| 555 |
+
loss = 0.7393267748270146
|
| 556 |
+
pearson = 0.6811194
|
| 557 |
+
rep_loss = 0.0
|
| 558 |
+
spearmanr = 0.6875245361344675
|
| 559 |
+
att_loss = 0.0
|
| 560 |
+
cls_loss = 0.7312956526916895
|
| 561 |
+
corr = 0.6956066943788616
|
| 562 |
+
eval_loss = 1.6437412532086069
|
| 563 |
+
global_step = 6299
|
| 564 |
+
loss = 0.7312956526916895
|
| 565 |
+
pearson = 0.6916644
|
| 566 |
+
rep_loss = 0.0
|
| 567 |
+
spearmanr = 0.6995489910412009
|
| 568 |
+
att_loss = 0.0
|
| 569 |
+
cls_loss = 0.7233900241390776
|
| 570 |
+
corr = 0.6906486794751315
|
| 571 |
+
eval_loss = 1.7348280599776735
|
| 572 |
+
global_step = 6399
|
| 573 |
+
loss = 0.7233900241390776
|
| 574 |
+
pearson = 0.6860321
|
| 575 |
+
rep_loss = 0.0
|
| 576 |
+
spearmanr = 0.6952652425371466
|
| 577 |
+
att_loss = 0.0
|
| 578 |
+
cls_loss = 0.7158463684912781
|
| 579 |
+
corr = 0.6854834754637844
|
| 580 |
+
eval_loss = 1.7626097811029313
|
| 581 |
+
global_step = 6499
|
| 582 |
+
loss = 0.7158463684912781
|
| 583 |
+
pearson = 0.68047786
|
| 584 |
+
rep_loss = 0.0
|
| 585 |
+
spearmanr = 0.6904890933378472
|
| 586 |
+
att_loss = 0.0
|
| 587 |
+
cls_loss = 0.708354945104738
|
| 588 |
+
corr = 0.6962654964689547
|
| 589 |
+
eval_loss = 1.7644097069476514
|
| 590 |
+
global_step = 6599
|
| 591 |
+
loss = 0.708354945104738
|
| 592 |
+
pearson = 0.6914344
|
| 593 |
+
rep_loss = 0.0
|
| 594 |
+
spearmanr = 0.7010966095455756
|
| 595 |
+
att_loss = 0.0
|
| 596 |
+
cls_loss = 0.7009560423588278
|
| 597 |
+
corr = 0.6954122807376282
|
| 598 |
+
eval_loss = 1.5823446055676074
|
| 599 |
+
global_step = 6699
|
| 600 |
+
loss = 0.7009560423588278
|
| 601 |
+
pearson = 0.69344985
|
| 602 |
+
rep_loss = 0.0
|
| 603 |
+
spearmanr = 0.6973747066244872
|
| 604 |
+
att_loss = 0.0
|
| 605 |
+
cls_loss = 0.6941643342006459
|
| 606 |
+
corr = 0.6776252117792276
|
| 607 |
+
eval_loss = 1.904833066970744
|
| 608 |
+
global_step = 6799
|
| 609 |
+
loss = 0.6941643342006459
|
| 610 |
+
pearson = 0.6721983
|
| 611 |
+
rep_loss = 0.0
|
| 612 |
+
spearmanr = 0.6830521279651937
|
| 613 |
+
att_loss = 0.0
|
| 614 |
+
cls_loss = 0.6876257611539878
|
| 615 |
+
corr = 0.6992549722251358
|
| 616 |
+
eval_loss = 1.5495127769226724
|
| 617 |
+
global_step = 6899
|
| 618 |
+
loss = 0.6876257611539878
|
| 619 |
+
pearson = 0.6976721
|
| 620 |
+
rep_loss = 0.0
|
| 621 |
+
spearmanr = 0.7008378157729033
|
| 622 |
+
att_loss = 0.0
|
| 623 |
+
cls_loss = 0.6814122569565901
|
| 624 |
+
corr = 0.6798451272470762
|
| 625 |
+
eval_loss = 1.7151304730709562
|
| 626 |
+
global_step = 6999
|
| 627 |
+
loss = 0.6814122569565901
|
| 628 |
+
pearson = 0.6775155
|
| 629 |
+
rep_loss = 0.0
|
| 630 |
+
spearmanr = 0.6821747477497678
|
| 631 |
+
att_loss = 0.0
|
| 632 |
+
cls_loss = 0.6750488731344202
|
| 633 |
+
corr = 0.6864478841023536
|
| 634 |
+
eval_loss = 1.7226520764066817
|
| 635 |
+
global_step = 7099
|
| 636 |
+
loss = 0.6750488731344202
|
| 637 |
+
pearson = 0.683116
|
| 638 |
+
rep_loss = 0.0
|
| 639 |
+
spearmanr = 0.6897797494325819
|
| 640 |
+
att_loss = 0.0
|
| 641 |
+
cls_loss = 0.6685966173770866
|
| 642 |
+
corr = 0.6961265942797831
|
| 643 |
+
eval_loss = 1.542426419384936
|
| 644 |
+
global_step = 7199
|
| 645 |
+
loss = 0.6685966173770866
|
| 646 |
+
pearson = 0.6937093
|
| 647 |
+
rep_loss = 0.0
|
| 648 |
+
spearmanr = 0.6985438746900898
|
| 649 |
+
att_loss = 0.0
|
| 650 |
+
cls_loss = 0.6625863695702197
|
| 651 |
+
corr = 0.672892541060939
|
| 652 |
+
eval_loss = 1.8842408143459481
|
| 653 |
+
global_step = 7299
|
| 654 |
+
loss = 0.6625863695702197
|
| 655 |
+
pearson = 0.6685181
|
| 656 |
+
rep_loss = 0.0
|
| 657 |
+
spearmanr = 0.6772669561109833
|
| 658 |
+
att_loss = 0.0
|
| 659 |
+
cls_loss = 0.6563814645868481
|
| 660 |
+
corr = 0.6909293282896121
|
| 661 |
+
eval_loss = 1.682561866146453
|
| 662 |
+
global_step = 7399
|
| 663 |
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loss = 0.6563814645868481
|
| 664 |
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pearson = 0.6861789
|
| 665 |
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rep_loss = 0.0
|
| 666 |
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|
| 667 |
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att_loss = 0.0
|
| 668 |
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|
| 669 |
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corr = 0.6774054586290517
|
| 670 |
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|
| 671 |
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global_step = 7499
|
| 672 |
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|
| 673 |
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|
| 674 |
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|
| 675 |
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|
| 676 |
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|
| 677 |
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|
| 678 |
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corr = 0.6780881167769086
|
| 679 |
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|
| 680 |
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global_step = 7599
|
| 681 |
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|
| 682 |
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|
| 683 |
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|
| 684 |
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|
| 685 |
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|
| 686 |
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cls_loss = 0.6387653072930873
|
| 687 |
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corr = 0.68327962031946
|
| 688 |
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|
| 689 |
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global_step = 7699
|
| 690 |
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|
| 691 |
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pearson = 0.6799519
|
| 692 |
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|
| 693 |
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|
| 694 |
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|
| 695 |
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|
| 696 |
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|
| 697 |
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|
| 698 |
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|
| 699 |
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|
| 700 |
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|
| 701 |
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|
| 702 |
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|
| 703 |
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|
| 704 |
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|
| 705 |
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|
| 706 |
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| 707 |
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|
| 708 |
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|
| 709 |
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|
| 710 |
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|
| 711 |
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|
| 712 |
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|
| 713 |
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|
| 714 |
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|
| 715 |
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|
| 716 |
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|
| 717 |
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|
| 718 |
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|
| 719 |
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|
| 720 |
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|
| 721 |
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|
| 722 |
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|
| 723 |
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|
| 724 |
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|
| 725 |
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global_step = 8099
|
| 726 |
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loss = 0.6178845111462368
|
| 727 |
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|
| 728 |
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|
| 729 |
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|
| 730 |
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|
| 731 |
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|
| 732 |
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corr = 0.6718672438686673
|
| 733 |
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|
| 734 |
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global_step = 8199
|
| 735 |
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loss = 0.6128612439000348
|
| 736 |
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pearson = 0.6708549
|
| 737 |
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rep_loss = 0.0
|
| 738 |
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spearmanr = 0.6728795616280207
|
| 739 |
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att_loss = 0.0
|
| 740 |
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|
| 741 |
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corr = 0.6651041147255143
|
| 742 |
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|
| 743 |
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global_step = 8299
|
| 744 |
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|
| 745 |
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|
| 746 |
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rep_loss = 0.0
|
| 747 |
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spearmanr = 0.6677330011413973
|
| 748 |
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att_loss = 0.0
|
| 749 |
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cls_loss = 0.6036006228428134
|
| 750 |
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corr = 0.6729532697228704
|
| 751 |
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eval_loss = 1.677842859258043
|
| 752 |
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global_step = 8399
|
| 753 |
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loss = 0.6036006228428134
|
| 754 |
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pearson = 0.67084026
|
| 755 |
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rep_loss = 0.0
|
| 756 |
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spearmanr = 0.6750662760790417
|
| 757 |
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att_loss = 0.0
|
| 758 |
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cls_loss = 0.5990938194672919
|
| 759 |
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corr = 0.6825831593473078
|
| 760 |
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| 761 |
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|
| 762 |
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|
| 763 |
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|
| 764 |
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rep_loss = 0.0
|
| 765 |
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| 766 |
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|
| 767 |
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cls_loss = 0.5946946106409213
|
| 768 |
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| 769 |
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| 770 |
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global_step = 8599
|
| 771 |
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| 772 |
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| 773 |
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rep_loss = 0.0
|
| 774 |
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| 775 |
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att_loss = 0.0
|
| 776 |
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| 777 |
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corr = 0.6657998324820606
|
| 778 |
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eval_loss = 1.7304384042607976
|
| 779 |
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global_step = 8699
|
| 780 |
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loss = 0.5904859170914621
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| 781 |
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pearson = 0.66438186
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| 782 |
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rep_loss = 0.0
|
| 783 |
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| 784 |
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att_loss = 0.0
|
| 785 |
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cls_loss = 0.5859172153921172
|
| 786 |
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corr = 0.6735087113115594
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| 787 |
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eval_loss = 1.743416058256271
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| 788 |
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global_step = 8799
|
| 789 |
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loss = 0.5859172153921172
|
| 790 |
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pearson = 0.6715877
|
| 791 |
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rep_loss = 0.0
|
| 792 |
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spearmanr = 0.6754297170109363
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| 793 |
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att_loss = 0.0
|
| 794 |
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cls_loss = 0.5816126147743282
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| 795 |
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corr = 0.6644848483214008
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| 796 |
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eval_loss = 1.732728586551991
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| 797 |
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global_step = 8899
|
| 798 |
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loss = 0.5816126147743282
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| 799 |
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pearson = 0.6625684
|
| 800 |
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rep_loss = 0.0
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| 801 |
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spearmanr = 0.6664013062733862
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| 802 |
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att_loss = 0.0
|
| 803 |
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cls_loss = 0.5775268228683409
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| 804 |
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corr = 0.6728886498907499
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| 805 |
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eval_loss = 1.764977162188672
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| 806 |
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global_step = 8999
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| 807 |
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| 808 |
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| 809 |
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rep_loss = 0.0
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| 810 |
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spearmanr = 0.6757325796086178
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| 811 |
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att_loss = 0.0
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| 812 |
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cls_loss = 0.5734869903849107
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| 813 |
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corr = 0.677398801426799
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| 814 |
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eval_loss = 1.7367773956440864
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| 815 |
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global_step = 9099
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| 816 |
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| 817 |
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| 818 |
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rep_loss = 0.0
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| 819 |
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spearmanr = 0.6797515165422576
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| 820 |
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att_loss = 0.0
|
| 821 |
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cls_loss = 0.5692596269704839
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| 822 |
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corr = 0.6674929723938927
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| 823 |
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eval_loss = 1.7240745539360858
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| 824 |
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global_step = 9199
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| 825 |
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loss = 0.5692596269704839
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| 826 |
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pearson = 0.6655415
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| 827 |
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rep_loss = 0.0
|
| 828 |
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spearmanr = 0.6694444151323289
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| 829 |
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att_loss = 0.0
|
| 830 |
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cls_loss = 0.5651277036054864
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| 831 |
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corr = 0.667139020828045
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| 832 |
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eval_loss = 1.7562614755427584
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| 833 |
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global_step = 9299
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| 834 |
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loss = 0.5651277036054864
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| 835 |
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pearson = 0.6648848
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| 836 |
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rep_loss = 0.0
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| 837 |
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spearmanr = 0.6693932359767688
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| 838 |
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att_loss = 0.0
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| 839 |
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cls_loss = 0.5613288295183084
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| 840 |
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corr = 0.6721675473345626
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| 841 |
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eval_loss = 1.7871363486381286
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| 842 |
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global_step = 9399
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| 843 |
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loss = 0.5613288295183084
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| 844 |
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pearson = 0.6692424
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| 845 |
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rep_loss = 0.0
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| 846 |
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spearmanr = 0.6750927126195647
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| 847 |
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att_loss = 0.0
|
| 848 |
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cls_loss = 0.5574137674542035
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| 849 |
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corr = 0.6725627390256492
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| 850 |
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eval_loss = 1.776785135903257
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| 851 |
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global_step = 9499
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| 852 |
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loss = 0.5574137674542035
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| 853 |
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pearson = 0.6695032
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| 854 |
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rep_loss = 0.0
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| 855 |
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spearmanr = 0.6756222660762007
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| 856 |
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att_loss = 0.0
|
| 857 |
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cls_loss = 0.5538221060552875
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| 858 |
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corr = 0.6762013154092168
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| 859 |
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eval_loss = 1.701874720289352
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| 860 |
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global_step = 9599
|
| 861 |
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loss = 0.5538221060552875
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| 862 |
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pearson = 0.6738435
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| 863 |
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rep_loss = 0.0
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| 864 |
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spearmanr = 0.6785591278200815
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| 865 |
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att_loss = 0.0
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| 866 |
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cls_loss = 0.5502476582192449
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| 867 |
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corr = 0.6725928902020977
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| 868 |
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eval_loss = 1.7757738150180655
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| 869 |
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global_step = 9699
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| 870 |
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loss = 0.5502476582192449
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| 871 |
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pearson = 0.6699413
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| 872 |
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rep_loss = 0.0
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| 873 |
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spearmanr = 0.6752444742899986
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| 874 |
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att_loss = 0.0
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| 875 |
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cls_loss = 0.5465871415224832
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| 876 |
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corr = 0.669948033281761
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| 877 |
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eval_loss = 1.7736153501145384
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| 878 |
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global_step = 9799
|
| 879 |
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loss = 0.5465871415224832
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| 880 |
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pearson = 0.66734093
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| 881 |
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rep_loss = 0.0
|
| 882 |
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spearmanr = 0.6725551322869412
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| 883 |
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att_loss = 0.0
|
| 884 |
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cls_loss = 0.5430337048390379
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| 885 |
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corr = 0.6690956343923434
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| 886 |
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eval_loss = 1.7552887017422534
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| 887 |
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global_step = 9899
|
| 888 |
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loss = 0.5430337048390379
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| 889 |
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pearson = 0.6664077
|
| 890 |
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rep_loss = 0.0
|
| 891 |
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spearmanr = 0.6717835644313543
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| 892 |
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att_loss = 0.0
|
| 893 |
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cls_loss = 0.5397035879905324
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| 894 |
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corr = 0.6711106084145703
|
| 895 |
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eval_loss = 1.7231389176338276
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| 896 |
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global_step = 9999
|
| 897 |
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loss = 0.5397035879905324
|
| 898 |
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pearson = 0.66858315
|
| 899 |
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rep_loss = 0.0
|
| 900 |
+
spearmanr = 0.6736380621507958
|
pytorch_model.bin
ADDED
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:cd5bf7626a31d1af38a6aefdbaff50d292ea6e12053a572290d201f880cfa159
|
| 3 |
+
size 58387432
|
vocab.txt
ADDED
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